Modeling the Predictive Social Mind

Hyperscanning shows friends explore and strangers converge in conversation

During conversation, people often endeavor to convey information in an understandable way (finding common ground) while also sharing novel or surprising information (exploring new ground). Here, we test how friends and strangers balance these two strategies to connect with each other. Using fMRI hyperscanning, we measure a preference for common ground as convergence over time and exploring new ground as divergence over time by tracking dyads' neural and linguistic trajectories over the course of semi-structured intimacy-building conversations. In our study, 60 dyads (30 friend dyads) engaged in a real-time conversation with discrete prompts and demarcated turns. Our analyses reveal that friends diverge neurally and linguistically: their neural patterns become more dissimilar over time and they explore more diverse topics. In contrast, strangers converge: neural patterns and language become more similar over time. The more a conversation between strangers resembles the exploratory conversations of friends, the more they enjoy it. Our results highlight exploring new ground as a strategy for a successful conversation.

Integrating stereotypes and factual evidence in interpersonal communication

Stereotypes can exert a powerful influence on our interactions with others, potentially leading to prejudice when factual evidence is ignored. Here, we identify neuroanatomical and developmental factors that influence the real-time integration of stereotypes and factual evidence during live social interactions. The study uses precisely quantified communicative exchanges in a longitudinal cohort of seventeen-year-olds followed since infancy, testing their ability to moderate stereotype tendencies toward children as contrary evidence accumulates. Our results indicate that the impact of stereotypes on communicative behavior is linked to individual variations in gray matter density and cortical thickness in the right anterior cingulate gyrus. In contrast, the ability to moderate stereotype tendencies is influenced by developmental exposure to social interactions during the initial years of life, beyond the effects of familial environment and later experiences. These findings pinpoint a key brain structure underlying stereotype tendencies and suggest that early-life social experiences have lasting consequences on how individuals integrate factual evidence in interpersonal communication.

Simplifying social learning

Social learning is complex, but people often seem to navigate social environments with ease. This ability creates a puzzle for traditional accounts of reinforcement learning (RL) that assume people negotiate a tradeoff between easy-but-simple behavior (model-free learning) and complex-but-difficult behavior (e.g., model-based learning). We offer a theoretical framework for resolving this puzzle: although social environments are complex, people have social expertise that helps them behave flexibly with low cognitive cost. Specifically, by using familiar concepts instead of focusing on novel details, people can turn hard learning problems into simpler ones. This ability highlights social learning as a prototype for studying cognitive simplicity in the face of environmental complexity and identifies a role for conceptual knowledge in everyday reward learning.

Motivation and prediction-driven processing of social memoranda

Social semantic memory guides many aspects of behavior. Individuals rely on acquired and inferred knowledge about personal characteristics and group membership to predict the behavior and character of social targets. These predictions then determine the expectations from, the behavior in, and the interpretations of social interactions. According to predictive processing accounts, mnemonic and attentional mechanisms should enhance the processing of prediction-violating events. However, empirical findings suggest that prediction-consistent social events are often better remembered. This mini-review integrates recent evidence from social and non-social memory research to highlight the role of motivation in explaining these discrepancies. A particular emphasis is given to the continuous nature of prediction-(in)consistency, the epistemic tendency of perceivers to maintain or update their knowledge, and the dynamic influences of motivation on multiple steps in prediction-driven social memory. The suggested framework provides a coherent outlook of existing work and offers promising future directions to better understand the ebb and flow of social memoranda.

Improved emotion differentiation under reduced acoustic variability of speech in autism

BACKGROUND

Socio-emotional impairments are among the diagnostic criteria for autism spectrum disorder (ASD), but the actual knowledge has substantiated both altered and intact emotional prosodies recognition. Here, a Bayesian framework of perception is considered suggesting that the oversampling of sensory evidence would impair perception within highly variable environments. However, reliable hierarchical structures for spectral and temporal cues would foster emotion discrimination by autistics.

METHODS

Event-related spectral perturbations (ERSP) extracted from electroencephalographic (EEG) data indexed the perception of anger, disgust, fear, happiness, neutral, and sadness prosodies while listening to speech uttered by (a) human or (b) synthesized voices characterized by reduced volatility and variability of acoustic environments. The assessment of mechanisms for perception was extended to the visual domain by analyzing the behavioral accuracy within a non-social task in which dynamics of precision weighting between bottom-up evidence and top-down inferences were emphasized. Eighty children (mean 9.7 years old; standard deviation 1.8) volunteered including 40 autistics. The symptomatology was assessed at the time of the study via the Autism Diagnostic Observation Schedule, Second Edition, and parents' responses on the Autism Spectrum Rating Scales. A mixed within-between analysis of variance was conducted to assess the effects of group (autism versus typical development), voice, emotions, and interaction between factors. A Bayesian analysis was implemented to quantify the evidence in favor of the null hypothesis in case of non-significance. Post hoc comparisons were corrected for multiple testing.

RESULTS

Autistic children presented impaired emotion differentiation while listening to speech uttered by human voices, which was improved when the acoustic volatility and variability of voices were reduced. Divergent neural patterns were observed from neurotypicals to autistics, emphasizing different mechanisms for perception. Accordingly, behavioral measurements on the visual task were consistent with the over-precision ascribed to the environmental variability (sensory processing) that weakened performance. Unlike autistic children, neurotypicals could differentiate emotions induced by all voices.

CONCLUSIONS

This study outlines behavioral and neurophysiological mechanisms that underpin responses to sensory variability. Neurobiological insights into the processing of emotional prosodies emphasized the potential of acoustically modified emotional prosodies to improve emotion differentiation by autistics.

TRIAL REGISTRATION

BioMed Central ISRCTN Registry, ISRCTN18117434. Registered on September 20, 2020.

Fear-related psychophysiological patterns are situation and individual dependent: A Bayesian model comparison approach

Is there a universal mapping of physiology to emotion, or do these mappings vary substantially by person or situation? Psychologists, philosophers, and neuroscientists have debated this question for decades. Most previous studies have focused on differentiating emotions on the basis of accompanying autonomic responses using analytical approaches that often assume within-category homogeneity. In the present study, we took an alternative approach to this question. We determined the extent to which the relationship between subjective experience and autonomic reactivity generalizes across, or depends upon, the individual and situation for instances of a single emotion category, specifically, fear. Electrodermal activity and cardiac activity-two autonomic measures that are often assumed to show robust relationships with instances of fear-were recorded while participants reported fear experience in response to dozens of fear-evoking videos related to three distinct situations: spiders, heights, and social encounters. We formally translated assumptions from diverse theoretical models into a common framework for model comparison analyses. Results exceedingly favored a model that assumed situation-dependency in the relationship between fear experience and autonomic reactivity, with subject variance also significant but constrained by situation. Models that assumed generalization across situations and/or individuals performed much worse by comparison. These results call into question the assumption of generalizability of autonomic-subjective mappings across instances of fear, as required in translational research from nonhuman animals to humans, and advance a situated approach to understanding the autonomic correlates of fear experience. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Overlapping representations of observed actions and action-related features

The lateral occipitotemporal cortex (LOTC) has been shown to capture the representational structure of a smaller range of actions. In the current study, we carried out an fMRI experiment in which we presented human participants with images depicting 100 different actions and used representational similarity analysis (RSA) to determine which brain regions capture the semantic action space established using judgments of action similarity. Moreover, to determine the contribution of a wide range of action-related features to the neural representation of the semantic action space we constructed an action feature model on the basis of ratings of 44 different features. We found that the semantic action space model and the action feature model are best captured by overlapping activation patterns in bilateral LOTC and ventral occipitotemporal cortex (VOTC). An RSA on eight dimensions resulting from principal component analysis carried out on the action feature model revealed partly overlapping representations within bilateral LOTC, VOTC, and the parietal lobe. Our results suggest spatially overlapping representations of the semantic action space of a wide range of actions and the corresponding action-related features. Together, our results add to our understanding of the kind of representations along the LOTC that support action understanding.

Asymmetric cognitive learning mechanisms underlying the persistence of intergroup bias

Intergroup bias, the tendency to favor ingroups and be hostile towards outgroups, underlies many societal problems and persists even when intergroup members interact and share experiences. Here we study the way cognitive learning processes contribute to the persistence of intergroup bias. Participants played a game with ingroup and outgroup bot-players that entailed collecting stars and could sacrifice a move to zap another player. We found that intergroup bias persisted as participants were more likely to zap outgroup players, regardless of their zapping behavior. Using a computational model, we found that this bias was caused by asymmetries in three learning mechanisms. Participants had a greater prior bias to zap out-group players, they learned more readily about the negative behavior of out-groups and were less likely to attribute the positive behavior of one out-group player to other out-group players. Our results uncover the way cognitive social learning mechanisms shape and confound intergroup dynamics.

Dynamic mutual predictions during social learning: A computational and interbrain model

During social interactions, we constantly learn about the thoughts, feelings, and personality traits of our interaction partners. Learning in social interactions is critical for bond formation and acquiring knowledge. Importantly, this type of learning is typically bi-directional, as both partners learn about each other simultaneously. Here we review the literature on social learning and propose a new computational and neural model characterizing mutual predictions that take place within and between interactions. According to our model, each partner in the interaction attempts to minimize the prediction error of the self and the interaction partner. In most cases, these inferential models become similar over time, thus enabling mutual understanding to develop. At the neural level, this type of social learning may be supported by interbrain plasticity, defined as a change in interbrain coupling over time in neural networks associated with social learning, among them the mentalizing network, the observation-execution system, and the hippocampus. The mutual prediction model constitutes a promising means of providing empirically verifiable accounts of how relationships develop over time.

Sex modulation of faces prediction error in the autistic brain

Recent research suggests that autistic females may have superior socio-cognitive abilities compared to autistic males, potentially contributing to underdiagnosis in females. However, it remains unclear whether these differences arise from distinct neurophysiological functioning in autistic males and females. This study addresses this question by presenting 41 autistic and 48 non-autistic adults with a spatially filtered faces oddball paradigm. Analysis of event-related potentials from scalp electroencephalography reveal a neurophysiological profile in autistic females that fell between those of autistic males and non-autistic females, highlighting sex differences in autism from the initial stages of face processing. This finding underscores the urgent need to explore neurophysiological sex differences in autism and encourages efforts toward a better comprehension of compensation mechanism and a clearer definition of what is meant by camouflaging.

Neural representations of situations and mental states are composed of sums of representations of the actions they afford

Human behavior depends on both internal and external factors. Internally, people's mental states motivate and govern their behavior. Externally, one's situation constrains which actions are appropriate or possible. To predict others' behavior, one must understand the influences of mental states and situations on actions. On this basis, we hypothesize that people represent situations and states in terms of associated actions. To test this, we use functional neuroimaging to estimate neural activity patterns associated with situations, mental states, and actions. We compute sums of the action patterns, weighted by how often each action occurs in each situation and state. We find that these summed action patterns reconstructed the corresponding situation and state patterns. These results suggest that neural representations of situations and mental states are composed of sums of their action affordances. Summed action representations thus offer a biological mechanism by which people can predict actions given internal and external factors.

Computational Social Psychology

Social psychologists attempt to explain how we interact by appealing to basic principles of how we think. To make good on this ambition, they are increasingly relying on an interconnected set of formal tools that model inference, attribution, value-guided decision making, and multi-agent interactions. By reviewing progress in each of these areas and highlighting the connections between them, we can better appreciate the structure of social thought and behavior, while also coming to understand when, why, and how formal tools can be useful for social psychologists.

Characterizing the mechanisms of social connection

Understanding how individuals form and maintain strong social networks has emerged as a significant public health priority as a result of the increased focus on the epidemic of loneliness and the myriad protective benefits conferred by social connection. In this review, we highlight the psychological and neural mechanisms that enable us to connect with others, which in turn help buffer against the consequences of stress and isolation. Central to this process is the experience of rewards derived from positive social interactions, which encourage the sharing of perspectives and preferences that unite individuals. Sharing affective states with others helps us to align our understanding of the world with another's, thereby continuing to reinforce bonds and strengthen relationships. These psychological processes depend on neural systems supporting reward and social cognitive function. Lastly, we also consider limitations associated with pursuing healthy social connections and outline potential avenues of future research.

Self-discrepancies in mind perception for actual, ideal, and ought selves and partners

Defining and measuring self-discrepancies in mind perception between how an individual sees their actual self in comparison to their ideal or ought self has a long but challenging history in psychology. Here we present a new approach for measuring and operationalizing discrepancies of mind by employing the mind perception framework that has been applied successfully to a variety of other psychological constructs. Across two studies (N = 265, N = 205), participants were recruited online to fill in a modified version of the mind perception survey with questions pertaining to three domains (actual, ideal, ought) and two agents (self versus partner). The results revealed that participants idealized and thought they ought to have greater agency (the ability to do) and diminished experience (the ability to feel) for both themselves and their partner. Sex differences were also examined across both studies, and while minor differences emerged, the effects were not robust across the collective evidence from both studies. The overall findings suggest that the mind perception approach can be used to distill a large number of qualities of mind into meaningful facets for interpretation in relation to self-discrepancy theory. This method can breathe new life into the field with future investigations directed at understanding self-discrepancies in relation to prosocial behaviour and psychological well-being.

Theory of collective mind

Theory of mind research has traditionally focused on the ascription of mental states to a single individual. Here, we introduce a theory of collective mind: the ascription of a unified mental state to a group of agents with convergent experiences. Rather than differentiation between one's personal perspective and that of another agent, a theory of collective mind requires perspectival unification across agents. We review recent scholarship across the cognitive sciences concerning the conceptual foundations of collective mind representations and their empirical induction through the synchronous arrival of shared information. Research suggests that representations of a collective mind cause psychological amplification of co-attended stimuli, create relational bonds, and increase cooperation, among co-attendees.

Egocentric Projection is a Rational Strategy for Accurate Emotion Prediction

People need to accurately understand and predict others' emotions in order to build and maintain meaningful social connections. However, when they encounter new social partners, people often do not have enough information about them to make accurate inferences. Rather, they often resort to an egocentric heuristic, and make predictions about a target by using their own self-knowledge as a proxy. Is this egocentric heuristic a form of cognitive bias, or is it a rational strategy for real-world social prediction? If egocentrism provides a rational and effective solution to the challenging task of social prediction in naturalistic contexts, we should expect that a) egocentric predictions tend to be more accurate, and b) people rely on self-knowledge to a greater extent when it's more likely to be a good proxy. Using an emotion prediction task and personality measures, we assessed similarity and predictive accuracy between first-year college students and their new acquaintance roommate. Results demonstrated that, when people need to predict an unfamiliar target's emotions, self-knowledge can often effectively approximate knowledge about others, and thus support accurate predictions. Moreover, participants that were typical of the sample, whose self-knowledge can better approximate information about the target, relied more on self-knowledge in their predictions, and thus achieved higher accuracy. These findings suggest that people rationally tune their use of egocentrism based on whether it is likely to pay off. Overall, these findings demonstrate a rational side to a cognitive phenomenon usually framed as a cognitive pitfall, namely egocentric projection, when its natural decision context is taken into consideration.

Transition dynamics shape mental state concepts

People have a unique ability to represent other people's internal thoughts and feelings-their mental states. Mental state knowledge has a rich conceptual structure, organized along key dimensions, such as valence. People use this conceptual structure to guide social interactions. How do people acquire their understanding of this structure? Here we investigate an underexplored contributor to this process: observation of mental state dynamics. Mental states-including both emotions and cognitive states-are not static. Rather, the transitions from one state to another are systematic and predictable. Drawing on prior cognitive science, we hypothesize that these transition dynamics may shape the conceptual structure that people learn to apply to mental states. Across nine behavioral experiments (N = 1,439), we tested whether the transition probabilities between mental states causally shape people's conceptual judgments of those states. In each study, we found that observing frequent transitions between mental states caused people to judge them to be conceptually similar. Computational modeling indicated that people translated mental state dynamics into concepts by embedding the states as points within a geometric space. The closer two states are within this space, the greater the likelihood of transitions between them. In three neural network experiments, we trained artificial neural networks to predict real human mental state dynamics. The networks spontaneously learned the same conceptual dimensions that people use to understand mental states. Together these results indicate that mental state dynamics-and the goal of predicting them-shape the structure of mental state concepts. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

What is (and was) a person? Evidence on historical mind perceptions from natural language

An important philosophical tradition identifies persons as those entities that have minds, such that mind perception is a window into person perception. Psychological research has found that human perceptions of mind consist of at least two distinct dimensions: agency (e.g. planning, deciding) and experience (e.g. feeling, hungering). Taking this insight into the semantic space of natural language, we develop a generalizable, scalable computational-linguistics method for measuring variation in perceived agency and experience in large archives of plain-text documents. The resulting text-based rankings of entities along these dimensions correspond to human judgments of perceived agency and experience assessed in blind surveys. We then map both dimensions of mind in historical English-language corpora over the last 200 years and identify two salient trends. First, we find that while women are now described as having similar levels of agency as men, they are still described as more experience-oriented. Second, we find that domesticated animals have gained higher attributions of experience (but not agency) relative to wild animals, especially since the rise of the global animal rights movement in the 1980s.

Functional role of the theory of mind network in integrating mentalistic prior information with action kinematics during action observation

Inferring intentions from verbal and nonverbal human behaviour is critical for everyday social life. Here, we combined Transcranial Magnetic Stimulation (TMS) with a behavioural priming paradigm to test whether key nodes of the Theory of Mind network (ToMn) contribute to understanding others' intentions by integrating prior knowledge about an agent with the observed action kinematics. We used a modified version of the Faked-Action Discrimination Task (FAD), a forced-choice paradigm in which participants watch videos of actors lifting a cube and judge whether the actors are trying to deceive them concerning the weight of the cube. Videos could be preceded or not by verbal description (prior) about the agent's truthful or deceitful intent. We applied single pulse TMS over three key nodes of the ToMn, namely dorsomedial prefrontal cortex (dmPFC), right posterior superior temporal sulcus (pSTS) and right temporo-parietal junction (rTPJ). Sham-TMS served as a control (baseline) condition. Following sham or rTPJ stimulation, we observed no consistent influence of priors on FAD performance. In contrast, following dmPFC stimulation, and to a lesser extent pSTS stimulation, truthful and deceitful actions were perceived as more deceptive only when the prior suggested a dishonest intention. These findings highlight a functional role of dmPFC and pSTS in coupling prior knowledge about deceptive intents with observed action kinematics in order to judge faked actions. Our study provides causal evidence that fronto-temporal nodes of the ToMn are functionally relevant to mental state inference during action observation.

Development of beliefs about censorship

Across four studies (total N = 431), we examined 5- to 10-year-old children's choices to censor depictions of harm. In all studies, children learned about (fictional) movies that depicted harmful behaviors and decided whether specific audiences should be allowed to watch those movies. In Study 1, children often censored depictions of harms and did so similarly when considering both themselves and another hypothetical child as the viewer. At the same time, children did not censor indiscriminately: Children censored depictions of intentional harms more than accidental harms and, in Study 2, children (and adults; N = 101) censored harms (especially intentional ones) more from younger versus older audiences. In Studies 3 and 4, we more directly tested children's motivations for censoring harms, examining dual potential motivations of 1) preventing viewers from feeling sad; and 2) preventing viewers from being inspired to engage in harmful behaviors. We found that children who were motivated to avoid inspiring harmful behaviors were especially likely to censor depictions of harmful intentions. Together, our results indicate that children make sophisticated decisions regarding censorship and underscore an early emerging motivation to disrupt cascades of harmful behavior. These findings hold implications for children's thinking about the psychological and behavioral consequences of harm and for children's thinking about the potential effects of media on themselves and others.

How unexpected events are processed in theory of mind regions: A conceptual replication

Recent research in social neuroscience has postulated that Theory of Mind (ToM) regions play a role in processing social prediction error (PE: the difference between what was expected and what was observed). Here, we tested whether PE signal depends on the type of prior information people use to make predictions - an agent's prior mental states (e.g., beliefs, desires, preferences) or an agent's prior behavior - as well as the type of information that confirms or violates such predictions. That is, does prior information about mental states (versus behavior) afford stronger predictions about an agent's subsequent mental states or behaviors? Additionally, when information about an agent's prior mental states or behavior is available, is PE signal strongest when information about an agent's subsequent mental state (vs behavior) is revealed? In line with prior research, results suggest that DMPFC, LTPJ, and RTPJ are recruited more for unexpected than expected outcomes. However, PE signal does not seem to discriminate on the basis of prior or outcome information type. These findings suggest that ToM regions may flexibly incorporate any available information to make predictions about, monitor, and perhaps explain, inconsistencies in social agents.

Virtue Discounting: Observability Reduces Moral Actors' Perceived Virtue

Performing prosociality in public presents a paradox: only by doing so can people demonstrate their virtue and also influence others through their example, yet observers may derogate actors' behavior as mere "virtue signaling." Here we investigate the role of observability of actors' behavior as one reason that people engage in such "virtue discounting." Further, we investigate observers' motivational inferences as a mechanism of this effect, using the comparison of generosity and fairness as a case study among virtues. Across 14 studies (7 preregistered, total N = 9,360), we show that public actors are perceived as less virtuous than private actors, and that this effect is stronger for generosity compared to fairness (i.e., differential virtue discounting). Exploratory factor analysis suggests that three types of motives-principled, reputation-signaling, and norm-signaling-affect virtue discounting. Using structural equation modeling, we show that observability's effect on actors' trait virtue ratings is largely explained by inferences that actors have less principled motivations. Further, we leverage experimental evidence to provide stronger causal evidence of these effects. We discuss theoretical and practical implications of our findings, as well as future directions for research on the social perception of virtue.

The cognitive structure underlying the organization of observed actions

In daily life, we frequently encounter actions performed by other people. Here we aimed to examine the key categories and features underlying the organization of a wide range of actions in three behavioral experiments (N = 378 participants). In Experiment 1, we used a multi-arrangement task of 100 different actions. Inverse multidimensional scaling and hierarchical clustering revealed 11 action categories, including Locomotion, Communication, and Aggressive actions. In Experiment 2, we used a feature-listing paradigm to obtain a wide range of action features that were subsequently reduced to 59 key features and used in a rating study (Experiment 3). A direct comparison of the feature ratings obtained in Experiment 3 between actions belonging to the categories identified in Experiment 1 revealed a number of features that appear to be critical for the distinction between these categories, e.g., the features Harm and Noise for the category Aggressive actions, and the features Targeting a person and Contact with others for the category Interaction. Finally, we found that a part of the category-based organization is explained by a combination of weighted features, whereas a significant proportion of variability remained unexplained, suggesting that there are additional sources of information that contribute to the categorization of observed actions. The characterization of action categories and their associated features serves as an important extension of previous studies examining the cognitive structure of actions. Moreover, our results may serve as the basis for future behavioral, neuroimaging and computational modeling studies.

Value-based neural representations predict social decision preferences

Social decision-making is omnipresent in everyday life, carrying the potential for both positive and negative consequences for the decision-maker and those closest to them. While evidence suggests that decision-makers use value-based heuristics to guide choice behavior, very little is known about how decision-makers' representations of other agents influence social choice behavior. We used multivariate pattern expression analyses on fMRI data to understand how value-based processes shape neural representations of those affected by one's social decisions and whether value-based encoding is associated with social decision preferences. We found that stronger value-based encoding of a given close other (e.g. parent) relative to a second close other (e.g. friend) was associated with a greater propensity to favor the former during subsequent social decision-making. These results are the first to our knowledge to explicitly show that value-based processes affect decision behavior via representations of close others.

The felt-presence experience: from cognition to the clinic

The felt presence experience is the basic feeling that someone else is present in the immediate environment, without clear sensory evidence. Ranging from benevolent to distressing, personified to ambiguous, felt presence has been observed in neurological case studies and within psychosis and paranoia, associated with sleep paralysis and anxiety, and recorded within endurance sports and spiritualist communities. In this Review, we summarise the philosophical, phenomenological, clinical, and non-clinical correlates of felt presence, as well as current approaches that use psychometric, cognitive, and neurophysiological methods. We present current mechanistic explanations for felt presence, suggest a unifying cognitive framework for the phenomenon, and discuss outstanding questions for the field. Felt presence offers a sublime opportunity to understand the cognitive neuroscience of own-body awareness and social agency detection, as an intuitive, but poorly understood, experience in health and disorder.

Formalising social representation to explain psychiatric symptoms

Recent work in social cognition has moved beyond a focus on how people process social rewards to examine how healthy people represent other agents and how this is altered in psychiatric disorders. However, formal modelling of social representation has not kept pace with these changes, impeding our understanding of how core aspects of social cognition function, and fail, in psychopathology. Here, we suggest that belief-based computational models provide a basis for an integrated sociocognitive approach to psychiatry, with the potential to address important but unexamined pathologies of social representation, such as maladaptive schemas and illusory social agents.

Learning from others is good, with others is better: the role of social interaction in human acquisition of new knowledge

Learning in humans is highly embedded in social interaction: since the very early stages of our lives, we form memories and acquire knowledge about the world from and with others. Yet, within cognitive science and neuroscience, human learning is mainly studied in isolation. The focus of past research in learning has been either exclusively on the learner or (less often) on the teacher, with the primary aim of determining developmental trajectories and/or effective teaching techniques. In fact, social interaction has rarely been explicitly taken as a variable of interest, despite being the medium through which learning occurs, especially in development, but also in adulthood. Here, we review behavioural and neuroimaging research on social human learning, specifically focusing on cognitive models of how we acquire semantic knowledge from and with others, and include both developmental as well as adult work. We then identify potential cognitive mechanisms that support social learning, and their neural correlates. The aim is to outline key new directions for experiments investigating how knowledge is acquired in its ecological niche, i.e. socially, within the framework of the two-person neuroscience approach. This article is part of the theme issue 'Concepts in interaction: social engagement and inner experiences'.

How We Understand Others: A Theory of How Social Perspective Taking Unfolds

Social perspective taking—the process through which perceivers discern the thoughts, feelings, and motivations of a target—is foundational for navigating social interactions, building relationships, maintaining mental health, promoting well-being, and a wide array of other desired outcomes. Despite its importance, little is known about how discrete social perspective taking attempts unfold. We propose a theory that the social perspective taking process consists of up to four distinguishable phases: perception of the target, motivation to engage in social perspective taking, strategy selection, and evaluation of the attempt. Scholars have emphasized two proximal outcomes of this process—social perspective taking effort and accuracy. We review the literature in support of these phases, noting the relative maturity of each area of research. In doing so, we hope this theory provides a framework for contextualizing how existing studies relate to one another across different subfields of psychology, facilitates testable predictions, prioritizes future investigations, and guides applied research designed to improve real-world social perspective taking.

Novel theory of mind task demonstrates representation of minds in mental state inference

Theory of mind (ToM), the ability to represent the mental states of oneself and others, is argued to be central to human social experience, and impairments in this ability are thought to underlie several psychiatric and developmental conditions. To examine the accuracy of mental state inferences, a novel ToM task was developed, requiring inferences to be made about the mental states of 'Targets', prior participants who took part in a videoed mock interview. Participants also made estimates of the Targets' personality traits. These inferences were compared to ground-truth data, provided by the Targets, of their true traits and mental states. Results from 55 adult participants demonstrated that trait inferences were used to derive mental state inferences, and that the accuracy of trait estimates predicted the accuracy of mental state inferences. Moreover, the size and direction of the association between trait accuracy and mental state accuracy varied according to the trait-mental state combination. The accuracy of trait inferences was predicted by the accuracy of participants' understanding of trait covariation at the population level. Findings are in accordance with the Mind-space theory, that representation of the Target mind is used in the inference of their mental states.

The influence of memory for impressions based on behaviours and beliefs on approach/avoidance decisions

Recent work has shown that memory for various types of information associated with social targets (impressions based on behaviours and political ideology) influences decisions to approach or avoid those same targets. The current study was intended to better understand the extent that memory for other types of details associated with targets (beliefs and behaviours) affects subsequent approach/avoidance decisions. In this investigation, participants formed impressions of social targets represented by a picture and a sentence (a belief in Experiment 1; either a belief or behaviour in Experiment 2). Later, memory for the impressions and sentences associated with each target was tested. Finally, participants decided whether they would want to approach or avoid each target. Results demonstrated that accurate memory strongly influenced approach/avoidance decisions for targets associated with different types of information (beliefs; behaviours), although there was no difference in the effect of memory between beliefs and behaviours. Overall, results suggest an important role of memory in decisions to approach or avoid others.

Exploring the Representational Structure of Trait Knowledge Using Perceived Similarity Judgments

A large body of past work has sought to identify the underlying dimensions that capture our trait knowledge of other people. However, the importance of particular traits in determining our overall impressions of others is not well understood, and different traits may be fundamental for impressions of famous versus unfamiliar people. For instance, we may focus on competence when evaluating a famous person, but on trustworthiness when evaluating a stranger. To examine the structure of overall impressions of famous people and of unfamiliar people, we probed the contributions of 13 different trait judgments to perceived similarity judgments. We found that different sets of traits best predicted perceived similarity between famous people versus between unfamiliar people; however, the relationship between each trait and perceived similarity generalized to some extent from famous people to unfamiliar people, suggesting a degree of overlap in the structure of overall impressions.

Evidence of the unidimensional structure of mind perception

The last decade has witnessed intense interest in how people perceive the minds of other entities (humans, non-human animals, and non-living objects and forces) and how this perception impacts behavior. Despite the attention paid to the topic, the psychological structure of mind perception-that is, the underlying properties that account for variance across judgements of entities-is not clear and extant reports conflict in terms of how to understand the structure. In the present research, we evaluated the psychological structure of mind perception by having participants evaluate a wide array of human, non-human animal, and non-animal entities. Using an entirely within-participants design, varied measurement approaches, and data-driven analyses, four studies demonstrated that mind perception is best conceptualized along a single dimension.

Planning with Theory of Mind

Understanding Theory of Mind should begin with an analysis of the problems it solves. The traditional answer is that Theory of Mind is used for predicting others' thoughts and actions. However, the same Theory of Mind is also used for planning to change others' thoughts and actions. Planning requires that Theory of Mind consists of abstract structured causal representations and supports efficient search and selection from innumerable possible actions. Theory of Mind contrasts with less cognitively demanding alternatives: statistical predictive models of other people's actions, or model-free reinforcement of actions by their effects on other people. Theory of Mind is likely used to plan novel interventions and predict their effects, for example, in pedagogy, emotion regulation, and impression management.

Incorporating social knowledge structures into computational models

To navigate social interactions successfully, humans need to continuously learn about the personality traits of other people (e.g., how helpful or aggressive is the other person?). However, formal models that capture the complexities of social learning processes are currently lacking. In this study, we specify and test potential strategies that humans can employ for learning about others. Standard Rescorla-Wagner (RW) learning models only capture parts of the learning process because they neglect inherent knowledge structures and omit previously acquired knowledge. We therefore formalize two social knowledge structures and implement them in hybrid RW models to test their usefulness across multiple social learning tasks. We name these concepts granularity (knowledge structures about personality traits that can be utilized at different levels of detail during learning) and reference points (previous knowledge formalized into representations of average people within a social group). In five behavioural experiments, results from model comparisons and statistical analyses indicate that participants efficiently combine the concepts of granularity and reference points-with the specific combinations in models depending on the people and traits that participants learned about. Overall, our experiments demonstrate that variants of RW algorithms, which incorporate social knowledge structures, describe crucial aspects of the dynamics at play when people interact with each other.

The promises and pitfalls of functional magnetic resonance imaging hyperscanning for social interaction research

Social neuroscience combines tools and perspectives from social psychology and neuroscience to understand how people interact with their social world. Here we discuss a relatively new method-hyperscanning-to study real-time, interactive social interactions using functional magnetic resonance imaging (fMRI). We highlight three contributions that fMRI hyperscanning makes to the study of the social mind: (1) Naturalism: it shifts the focus from tightly-controlled stimuli to more naturalistic social interactions; (2) Multi-person Dynamics: it shifts the focus from individuals as the unit of analysis to dyads and groups; and (3) Neural Resolution: fMRI hyperscanning captures high-resolution neural patterns and dynamics across the whole brain, unlike other neuroimaging hyperscanning methods (e.g., electroencephalogram, functional near-infrared spectroscopy). Finally, we describe the practical considerations and challenges that fMRI hyperscanning researchers must navigate. We hope researchers will harness this powerful new paradigm to address pressing questions in today's society.

The reciprocal relationship between episodic memory and future thinking: How the outcome of predictions is subsequently remembered

Evidence suggests that memory is involved in making simulations and predictions about the future (i.e., future thinking), but less work has examined how the outcome of those predictions (whether events play out as predicted or expected) subsequently affects episodic memory. In this investigation, we examine whether memory is better for outcomes that are consistent with predictions, or whether memory is enhanced for outcomes that are inconsistent with predictions, after the predicted event occurs. In this experiment, participants learned a core trait associated with social targets (e.g., high in extroversion), before making predictions about behaviors targets would perform. Participants then were shown behaviors the social targets actually performed (i.e., prediction outcome), which was either consistent or inconsistent with predictions. After that, participants completed a memory test (recognition; recall) for the prediction outcomes. For recognition, the results revealed better memory for outcomes that were consistent with traits associated with targets (i.e., trait-consistent outcomes), compared to outcomes that were inconsistent (i.e., trait-inconsistent outcomes). Finding a memory advantage for trait-consistent outcomes suggests that outcomes that are in line with the contents of memory (e.g., what one knows; schemas) are more readily remembered than those that are inconsistent with memory, which may reflect an adaptive memory process. For recall, memory did not differ between trait-consistent and trait-inconsistent outcomes. Altogether, the results of this experiment advance understanding of the reciprocal relationship between episodic memory and future thinking and show that outcome of predictions has an influence on subsequent episodic memory, at least as measured by recognition.

Atypical cerebellar functional connectivity at 9 months of age predicts delayed socio-communicative profiles in infants at high and low risk for autism

BACKGROUND

While the cerebellum is traditionally known for its role in sensorimotor control, emerging research shows that particular subregions, such as right Crus I (RCrusI), support language and social processing. Indeed, cerebellar atypicalities are commonly reported in autism spectrum disorder (ASD), a neurodevelopmental disorder characterized by socio-communicative impairments. However, the cerebellum's contribution to early socio-communicative development remains virtually unknown.

METHODS

Here, we characterized functional connectivity within cerebro-cerebellar networks implicated in language/social functions in 9-month-old infants who exhibit distinct 3-year socio-communicative developmental profiles. We employed a data-driven clustering approach to stratify our sample of infants at high (n = 82) and low (n = 37) familial risk for ASD into three cohorts-Delayed, Late-Blooming, and Typical-who showed unique socio-communicative trajectories. We then compared the cohorts on indices of language and social development. Seed-based functional connectivity analyses with RCrusI were conducted on infants with fMRI data (n = 66). Cohorts were compared on connectivity estimates from a-priori regions, selected on the basis of reported coactivation with RCrusI during language/social tasks.

RESULTS

The three trajectory-based cohorts broadly differed in social communication development, as evidenced by robust differences on numerous indices of language and social skills. Importantly, at 9 months, the cohorts showed striking differences in cerebro-cerebellar circuits implicated in language/social functions. For all regions examined, the Delayed cohort exhibited significantly weaker RCrusI connectivity compared to both the Late-Blooming and Typical cohorts, with no significant differences between the latter cohorts.

CONCLUSIONS

We show that hypoconnectivity within distinct cerebro-cerebellar networks in infancy predicts altered socio-communicative development before delays overtly manifest, which may be relevant for early detection and intervention. As the cerebellum is implicated in prediction, our findings point to probabilistic learning as a potential intermediary mechanism that may be disrupted in infancy, cascading into alterations in social communication.

Predicting and remembering the behaviors of social targets: how prediction accuracy affects episodic memory

BACKGROUND

Decades of research has investigated the relationship between memory and future thinking. Although some of this work has shown that memory forms the basis of making predictions about the future, less work has investigated how the outcome of those predictions (whether consistent or inconsistent with what one predicts) is later remembered. Limited past works suggests that memory for outcomes that are consistent with what one predicts are better remembered that predictions that are inconsistent. To advance understanding of the relationship between episodic memory and future thinking, the current investigation examines how the outcome of predictions affects memory after the predicted events takes place.

METHODS

In this experiment, participants first learned trait information about social targets. Then, participants imagined scenarios involving targets and the self (i.e., the participant) and made predictions about which behaviors targets would perform based on the trait information associated with targets participants learned earlier. Participants were then told the behaviors the targets actually performed (i.e., prediction outcome), which was either consistent or inconsistent with predictions, before then taking a memory test for prediction outcomes (what the social target actually did).

RESULTS

Results showed memory for prediction-consistent outcomes was better than for prediction-inconsistent outcomes, suggesting people exhibit enhanced memory for events that are in line with predictions based on existing contents of memory (e.g., what one knows; schemas), which is in line with the limited past work in this domain.

CONCLUSION

Overall, finding better memory for prediction-consistent outcomes may reflect an adaptive function in memory, where people show enhanced memory for episodes when they play out as predicted, and aligned with the current contents of memory.

Electrocorticographic evidence of a common neurocognitive sequence for mentalizing about the self and others

Neuroimaging studies of mentalizing (i.e., theory of mind) consistently implicate the default mode network (DMN). Nevertheless, the social cognitive functions of individual DMN regions remain unclear, perhaps due to limited spatiotemporal resolution in neuroimaging. Here we use electrocorticography (ECoG) to directly record neuronal population activity while 16 human participants judge the psychological traits of themselves and others. Self- and other-mentalizing recruit near-identical cortical sites in a common spatiotemporal sequence. Activations begin in the visual cortex, followed by temporoparietal DMN regions, then finally in medial prefrontal regions. Moreover, regions with later activations exhibit stronger functional specificity for mentalizing, stronger associations with behavioral responses, and stronger self/other differentiation. Specifically, other-mentalizing evokes slower and longer activations than self-mentalizing across successive DMN regions, implying lengthier processing at higher levels of representation. Our results suggest a common neurocognitive pathway for self- and other-mentalizing that follows a complex spatiotemporal gradient of functional specialization across DMN and beyond.

The paradox of social interaction: Shared intentionality, we-reasoning, and virtual bargaining

Social interaction is both ubiquitous and central to understanding human behavior. Such interactions depend, we argue, on shared intentionality: the parties must form a common understanding of an ambiguous interaction (e.g., one person giving a present to another requires that both parties appreciate that a voluntary transfer of ownership is intended). Yet how can shared intentionality arise? Many well-known accounts of social cognition, including those involving "mind-reading," typically fall into circularity and/or regress. For example, A's beliefs and behavior may depend on her prediction of B's beliefs and behavior, but B's beliefs and behavior depend in turn on her prediction of A's beliefs and behavior. One possibility is to embrace circularity and take shared intentionality as imposing consistency conditions on beliefs and behavior, but typically there are many possible solutions and no clear criteria for choosing between them. We argue that addressing these challenges requires some form of we-reasoning, but that this raises the puzzle of how the collective agent (the "we") arises from the individual agents. This puzzle can be solved by proposing that the will of the collective agent arises from a simulated process of bargaining: agents must infer what they would agree, were they able to communicate. This model explains how, and which, shared intentions are formed. We also propose that such "virtual bargaining" may be fundamental to understanding social interactions. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Minority salience and the overestimation of individuals from minority groups in perception and memory

Our cognitive system is tuned toward spotting the uncommon and unexpected. We propose that individuals coming from minority groups are, by definition, just that—uncommon and often unexpected. Consequently, they are psychologically salient in perception, memory, and visual awareness. This minority salience creates a tendency to overestimate the prevalence of minorities, leading to an erroneous picture of our social environments—an illusion of diversity. In 12 experiments with 942 participants, we found evidence that the presence of minority group members is indeed overestimated in memory and perception and that masked images of minority group members are prioritized for visual awareness. These findings were consistent when participants were members of both the majority group and the minority group. Moreover, this overestimated prevalence of minorities led to decreased support for diversity-promoting policies. We discuss the theoretical implications of the illusion of diversity and how it may inform more equitable and inclusive decision-making.

Computational and Motivational Mechanisms of Human Social Decision Making Involving Close Others

Every day, human beings make decisions with social consequences. These social consequences matter most when they impact those closest to us. Recent research has shown that humans exhibit reliable preferences when deciding between conflicting outcomes involving close others - for example, prioritizing the interests of one's family member over one's friend. However, virtually nothing is known about the mechanisms that drive these preferences. We conducted a pre-registered study in a large (maximum N=375) sample to quantify the computational and motivational mechanisms of human social decision-making preferences involving close others. By pairing assessment techniques from behavioral economics and psychological science with computational modeling and random coefficient regression, we show that value-based cognitive computations (e.g., risk and loss aversion) drive social decision-making preferences involving financial outcomes, whereas socioemotional motivations (e.g., relationship quality) underlie preferences involving social outcomes. These results imply mechanistic heterogeneity, underscoring a need for greater attention to contextual specificity in social decision-making.

The 3d Mind Model characterizes how people understand mental states across modern and historical cultures

Humans rely on social interaction to achieve many important goals. These interactions rely in turn on people's capacity to understand others' mental states: their thoughts and feelings. Do different cultures understand minds in different ways, or do widely shared principles describe how different cultures understand mental states? Extensive data suggest that the mind organizes mental state concepts using the 3d Mind Model, composed of the psychological dimensions: rationality (vs. emotionality), social impact (states which affect others more vs. less), and valence (positive vs. negative states). However, this evidence comes primarily from English-speaking individuals in the United States. Here we investigated mental state representation in 57 contemporary countries, using 163 million English language tweets; in 17 languages, using billions of words of text from internet webpages; and across more than 2000 years of history, using curated texts from four historical societies. We quantified mental state meaning by analyzing the text produced by each culture using word embeddings. We then tested whether the 3d Mind Model could explain which mental states were similar in meaning within each culture. We found that the 3d Mind Model significantly explained mental state meaning in every country, language, and historical society that we examined. These results suggest that rationality, social impact, and valence form a generalizable conceptual backbone for mental state representation.

Theory of mind in dysphoric and non--dysphoric adults: An ERP study of true-- and false--belief reasoning

Theory of mind (ToM) - the understanding that others' behaviors are connected with internal mental states - is an important part of everyday social cognition. There is increasing behavioral evidence that ToM reasoning can be affected by mood. To gain insight into the ways sad mood may affect the underlying mechanisms of ToM reasoning, we recorded event-related brain potentials (ERPs) as dysphoric (N = 16) and non-dysphoric (N = 24) participants reasoned about a protagonist's true or false beliefs about an object's location. Results showed significant group effects on early components of the ERP - individuals in the dysphoric group showed greater amplitudes for the anterior N1 and N2/P2 components relative to those in the non-dysphoric group. Later in the ERP, non-dysphoric individuals showed evidence of neurocognitive dissociations between true and false belief. Dysphoric individuals, however, did not show evidence for these later dissociations. This evidence suggests that dysphoria may be associated with effortful reasoning about other's mental states, even when that effort is not necessary (i.e., when reasoning about true beliefs). We discuss the implications of these findings for understanding how mood affects ToM reasoning and for how especially deliberative ToM processing in dysphoria may lead to social difficulties.

Adaptive Empathy: A Model for Learning Empathic Responses in Response to Feedback

Empathy is usually deployed in social interactions. Nevertheless, common measures and examinations of empathy study this construct in isolation from the person in distress. In this article we seek to extend the field of examination to include both empathizer and target to determine whether and how empathic responses are affected by feedback and learned through interaction. Building on computational approaches in feedback-based adaptations (e.g., no feedback, model-free and model-based learning), we propose a framework for understanding how empathic responses are learned on the basis of feedback. In this framework, adaptive empathy, defined as the ability to adapt one's empathic responses, is a central aspect of empathic skills and can provide a new dimension to the evaluation and investigation of empathy. By extending existing neural models of empathy, we suggest that adaptive empathy may be mediated by interactions between the neural circuits associated with valuation, shared distress, observation-execution, and mentalizing. Finally, we propose that adaptive empathy should be considered a prominent facet of empathic capabilities with the potential to explain empathic behavior in health and psychopathology.

Prefrontal contributions to the stability and variability of thought and conscious experience

The human prefrontal cortex is a structurally and functionally heterogenous brain region, including multiple subregions that have been linked to different large-scale brain networks. It contributes to a broad range of mental phenomena, from goal-directed thought and executive functions to mind-wandering and psychedelic experience. Here we review what is known about the functions of different prefrontal subregions and their affiliations with large-scale brain networks to examine how they may differentially contribute to the diversity of mental phenomena associated with prefrontal function. An important dimension that distinguishes across different kinds of conscious experience is the stability or variability of mental states across time. This dimension is a central feature of two recently introduced theoretical frameworks-the dynamic framework of thought (DFT) and the relaxed beliefs under psychedelics (REBUS) model-that treat neurocognitive dynamics as central to understanding and distinguishing between different mental phenomena. Here, we bring these two frameworks together to provide a synthesis of how prefrontal subregions may differentially contribute to the stability and variability of thought and conscious experience. We close by considering future directions for this work.

Person Memory Mechanism Underlying Approach and Avoidance Judgments of Social Targets

People display approach and avoidance tendencies toward social targets. Although much research has studied the factors that affect decisions to approach or avoid targets, less work has investigated whether cognitive factors, such as episodic memory (e.g., details remembered about others from previous encounters) contribute to such judgments. Across two experiments, participants formed positive or negative impressions of targets based on their picture, a trait-implying behavior (Experiments 1 & 2), and their political ideology (conservative or liberal; Experiment 2). Memory and approach/avoidance decisions for targets were then measured. Results showed remembering negative impressions about targets increased avoidance responses, whereas remembering positive impressions increased approach responses. Strikingly, falsely remembering negative impressions for novel social targets (not seen before) also induced avoidance. Results suggest remembering negative information about targets, whether correctly or falsely, strongly influences future social judgments. Overall, these data support an episodic memory mechanism underlying subsequent approach/avoidance judgments, which is a rich area for future research.